Abstract
ABSTRACT This study adopts association rules to identify the co-occurrence of attributes concerned by inbound tourists visiting scenic spots and further make a cluster analysis. In total, 72,890 online reviews of 218 scenic spots in China from inbound travelers from TripAdvisor used for analysis. It is found that the tourists could be clustered into three groups: view-sensitive travelers, crowding-sensitive travelers, and price-sensitive travelers. This study makes an early attempt to cluster travelers according to their conjoint preference patterns based on the co-occurrence of destination attributes, and provides a new multi-attribute approach to the investigation of tourist preferences and market segmentation.
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